Haim Sompolinsky - Publications

Affiliations: 
Hebrew University, Jerusalem, Jerusalem, Israel 
Website:
http://neurophysics.huji.ac.il/~haim/

105 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2021 Ginosar G, Aljadeff J, Burak Y, Sompolinsky H, Las L, Ulanovsky N. Locally ordered representation of 3D space in the entorhinal cortex. Nature. PMID 34381211 DOI: 10.1038/s41586-021-03783-x  0.58
2020 Advani MS, Saxe AM, Sompolinsky H. High-dimensional dynamics of generalization error in neural networks. Neural Networks : the Official Journal of the International Neural Network Society. 132: 428-446. PMID 33022471 DOI: 10.1016/j.neunet.2020.08.022  0.409
2020 Cohen U, Chung S, Lee DD, Sompolinsky H. Separability and geometry of object manifolds in deep neural networks. Nature Communications. 11: 746. PMID 32029727 DOI: 10.1038/S41467-020-14578-5  0.773
2019 Maor I, Shwartz-Ziv R, Feigin L, Elyada Y, Sompolinsky H, Mizrahi A. Neural Correlates of Learning Pure Tones or Natural Sounds in the Auditory Cortex. Frontiers in Neural Circuits. 13: 82. PMID 32047424 DOI: 10.3389/fncir.2019.00082  0.344
2019 Gjorgjieva J, Meister M, Sompolinsky H. Functional diversity among sensory neurons from efficient coding principles. Plos Computational Biology. 15: e1007476. PMID 31725714 DOI: 10.1371/Journal.Pcbi.1007476  0.525
2018 Landau ID, Sompolinsky H. Coherent chaos in a recurrent neural network with structured connectivity. Plos Computational Biology. 14: e1006309. PMID 30543634 DOI: 10.1371/journal.pcbi.1006309  0.388
2018 Chen X, Mu Y, Hu Y, Kuan AT, Nikitchenko M, Randlett O, Chen AB, Gavornik JP, Sompolinsky H, Engert F, Ahrens MB. Brain-wide Organization of Neuronal Activity and Convergent Sensorimotor Transformations in Larval Zebrafish. Neuron. 100: 876-890.e5. PMID 30473013 DOI: 10.1016/J.Neuron.2018.09.042  0.32
2018 Chung S, Cohen U, Sompolinsky H, Lee DD. Learning Data Manifolds with a Cutting Plane Method. Neural Computation. 1-23. PMID 30148702 DOI: 10.1162/Neco_A_01119  0.744
2018 Chung S, Lee DD, Sompolinsky H. Classification and Geometry of General Perceptual Manifolds Physical Review X. 8. DOI: 10.1103/PhysRevX.8.031003  0.787
2017 Rubin R, Abbott LF, Sompolinsky H. Balanced excitation and inhibition are required for high-capacity, noise-robust neuronal selectivity. Proceedings of the National Academy of Sciences of the United States of America. PMID 29042519 DOI: 10.1073/pnas.1705841114  0.617
2017 Litwin-Kumar A, Harris KD, Axel R, Sompolinsky H, Abbott LF. Optimal Degrees of Synaptic Connectivity. Neuron. PMID 28215558 DOI: 10.1016/J.Neuron.2017.01.030  0.574
2016 Landau ID, Egger R, Dercksen VJ, Oberlaender M, Sompolinsky H. The Impact of Structural Heterogeneity on Excitation-Inhibition Balance in Cortical Networks. Neuron. PMID 27866797 DOI: 10.1016/J.Neuron.2016.10.027  0.34
2016 Naumann EA, Fitzgerald JE, Dunn TW, Rihel J, Sompolinsky H, Engert F. From Whole-Brain Data to Functional Circuit Models: The Zebrafish Optomotor Response. Cell. 167: 947-960.e20. PMID 27814522 DOI: 10.1016/J.Cell.2016.10.019  0.309
2016 Sharpee TO, Destexhe A, Kawato M, Sekulić V, Skinner FK, Wójcik DK, Chintaluri C, Cserpán D, Somogyvári Z, Kim JK, Kilpatrick ZP, Bennett MR, Josić K, Elices I, Arroyo D, ... ... Sompolinsky H, et al. 25th Annual Computational Neuroscience Meeting: CNS-2016 Bmc Neuroscience. 17: 54. PMID 27534393 DOI: 10.1186/S12868-016-0283-6  0.726
2016 Chung S, Lee DD, Sompolinsky H. Linear readout of object manifolds. Physical Review. E. 93: 060301. PMID 27415193 DOI: 10.1103/PhysRevE.93.060301  0.787
2015 Kadmon J, Sompolinsky H. Transition to chaos in random neuronal networks Physical Review X. 5. DOI: 10.1103/PhysRevX.5.041030  0.404
2014 Stern M, Sompolinsky H, Abbott LF. Dynamics of random neural networks with bistable units. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics. 90: 062710. PMID 25615132 DOI: 10.1103/PhysRevE.90.062710  0.603
2014 Gjorgjieva J, Sompolinsky H, Meister M. Benefits of pathway splitting in sensory coding. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 34: 12127-44. PMID 25186757 DOI: 10.1523/Jneurosci.1032-14.2014  0.53
2014 Babadi B, Sompolinsky H. Sparseness and expansion in sensory representations. Neuron. 83: 1213-26. PMID 25155954 DOI: 10.1016/j.neuron.2014.07.035  0.36
2014 Memmesheimer RM, Rubin R, Olveczky BP, Sompolinsky H. Learning precisely timed spikes. Neuron. 82: 925-38. PMID 24768299 DOI: 10.1016/j.neuron.2014.03.026  0.391
2014 Sompolinsky H. Computational neuroscience: beyond the local circuit. Current Opinion in Neurobiology. 25: xiii-xviii. PMID 24602868 DOI: 10.1016/j.conb.2014.02.002  0.389
2014 Pehlevan C, Sompolinsky H. Selectivity and sparseness in randomly connected balanced networks. Plos One. 9: e89992. PMID 24587172 DOI: 10.1371/Journal.Pone.0089992  0.76
2013 Gütig R, Gollisch T, Sompolinsky H, Meister M. Computing complex visual features with retinal spike times. Plos One. 8: e53063. PMID 23301021 DOI: 10.1371/journal.pone.0053063  0.489
2012 Ganguli S, Sompolinsky H. Compressed sensing, sparsity, and dimensionality in neuronal information processing and data analysis. Annual Review of Neuroscience. 35: 485-508. PMID 22483042 DOI: 10.1146/Annurev-Neuro-062111-150410  0.326
2012 Rokni U, Sompolinsky H. How the brain generates movement. Neural Computation. 24: 289-331. PMID 22023199 DOI: 10.1162/NECO_a_00223  0.335
2011 Abbott LF, Rajan K, Sompolinsky H. Interactions between Intrinsic and Stimulus-Evoked Activity in Recurrent Neural Networks The Dynamic Brain: An Exploration of Neuronal Variability and Its Functional Significance. DOI: 10.1093/acprof:oso/9780195393798.003.0004  0.53
2011 Burak Y, Rokni U, Meister M, Sompolinsky H. Reply to Wehrhahn: Experimental requirements for testing the role of peripheral cues in dynamic image stabilization Proceedings of the National Academy of Sciences of the United States of America. 108: E36. DOI: 10.1073/Pnas.1100198108  0.684
2010 Rubin R, Monasson R, Sompolinsky H. Theory of spike timing-based neural classifiers. Physical Review Letters. 105: 218102. PMID 21231357 DOI: 10.1103/Physrevlett.105.218102  0.356
2010 Burak Y, Rokni U, Meister M, Sompolinsky H. Bayesian model of dynamic image stabilization in the visual system. Proceedings of the National Academy of Sciences of the United States of America. 107: 19525-30. PMID 20937893 DOI: 10.1073/Pnas.1006076107  0.662
2010 Rajan K, Abbott LF, Sompolinsky H. Stimulus-dependent suppression of chaos in recurrent neural networks. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics. 82: 011903. PMID 20866644 DOI: 10.1103/PhysRevE.82.011903  0.607
2010 Rajan K, Abbott LF, Sompolinsky H. Stimulus-dependent suppression of intrinsic variability in recurrent neural networks Bmc Neuroscience. 11. DOI: 10.1186/1471-2202-11-S1-O17  0.417
2010 Rajan K, Abbott LF, Sompolinsky H. Inferring stimulus selectivity from the spatial structure of neural network dynamics Advances in Neural Information Processing Systems 23: 24th Annual Conference On Neural Information Processing Systems 2010, Nips 2010 0.531
2009 Burak Y, Lewallen S, Sompolinsky H. Stimulus-dependent correlations in threshold-crossing spiking neurons. Neural Computation. 21: 2269-308. PMID 19409055 DOI: 10.1162/Neco.2009.07-08-830  0.65
2008 Ganguli S, Huh D, Sompolinsky H. Memory traces in dynamical systems. Proceedings of the National Academy of Sciences of the United States of America. 105: 18970-5. PMID 19020074 DOI: 10.1073/Pnas.0804451105  0.599
2007 Pitkow X, Sompolinsky H, Meister M. A neural computation for visual acuity in the presence of eye movements. Plos Biology. 5: e331. PMID 18162043 DOI: 10.1371/Journal.Pbio.0050331  0.757
2006 Shamir M, Sompolinsky H. Implications of neuronal diversity on population coding. Neural Computation. 18: 1951-86. PMID 16771659 DOI: 10.1162/neco.2006.18.8.1951  0.368
2006 Gütig R, Sompolinsky H. The tempotron: a neuron that learns spike timing-based decisions. Nature Neuroscience. 9: 420-8. PMID 16474393 DOI: 10.1038/nn1643  0.37
2006 Loewenstein Y, Mahon S, Chadderton P, Kitamura K, Sompolinsky H, Yarom Y, Häusser M. Loewenstein et al. reply [2] Nature Neuroscience. 9: 461. DOI: 10.1038/nn0406-461  0.731
2005 Loewenstein Y, Mahon S, Chadderton P, Kitamura K, Sompolinsky H, Yarom Y, Häusser M. Bistability of cerebellar Purkinje cells modulated by sensory stimulation. Nature Neuroscience. 8: 202-11. PMID 15665875 DOI: 10.1038/nn1393  0.782
2005 van Vreeswijk C, Sompolinsky H. Course 9 Irregular activity in large networks of neurons Les Houches Summer School Proceedings. 80: 341-406. DOI: 10.1016/S0924-8099(05)80015-0  0.708
2004 Goldberg JA, Rokni U, Sompolinsky H. Patterns of ongoing activity and the functional architecture of the primary visual cortex. Neuron. 42: 489-500. PMID 15134644 DOI: 10.1016/S0896-6273(04)00197-7  0.598
2004 Shamir M, Sompolinsky H. Nonlinear population codes. Neural Computation. 16: 1105-36. PMID 15130244 DOI: 10.1162/089976604773717559  0.348
2004 White OL, Lee DD, Sompolinsky H. Short-term memory in orthogonal neural networks. Physical Review Letters. 92: 148102. PMID 15089576 DOI: 10.1103/Physrevlett.92.148102  0.511
2004 Kang K, Shapley RM, Sompolinsky H. Information tuning of populations of neurons in primary visual cortex. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 24: 3726-35. PMID 15084652 DOI: 10.1523/JNEUROSCI.4272-03.2004  0.352
2003 Shriki O, Hansel D, Sompolinsky H. Rate models for conductance-based cortical neuronal networks. Neural Computation. 15: 1809-41. PMID 14511514 DOI: 10.1162/08997660360675053  0.786
2003 Loewenstein Y, Sompolinsky H. Temporal integration by calcium dynamics in a model neuron. Nature Neuroscience. 6: 961-7. PMID 12937421 DOI: 10.1038/nn1109  0.758
2003 Gütig R, Aharonov R, Rotter S, Sompolinsky H. Learning input correlations through nonlinear temporally asymmetric Hebbian plasticity. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 23: 3697-714. PMID 12736341 DOI: 10.1523/Jneurosci.23-09-03697.2003  0.313
2003 Litvak V, Sompolinsky H, Segev I, Abeles M. On the transmission of rate code in long feedforward networks with excitatory-inhibitory balance. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 23: 3006-15. PMID 12684488 DOI: 10.1523/Jneurosci.23-07-03006.2003  0.577
2003 Kang K, Shelley M, Sompolinsky H. Mexican hats and pinwheels in visual cortex. Proceedings of the National Academy of Sciences of the United States of America. 100: 2848-53. PMID 12601163 DOI: 10.1073/Pnas.0138051100  0.344
2002 Loewenstein Y, Sompolinsky H. Oscillations by symmetry breaking in homogeneous networks with electrical coupling. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics. 65: 051926. PMID 12059612 DOI: 10.1103/PhysRevE.65.051926  0.763
2001 Sompolinsky H, Yoon H, Kang K, Shamir M. Population coding in neuronal systems with correlated noise. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics. 64: 051904. PMID 11735965 DOI: 10.1103/Physreve.64.051904  0.332
2001 Loewenstein Y, Yarom Y, Sompolinsky H. The generation of oscillations in networks of electrically coupled cells. Proceedings of the National Academy of Sciences of the United States of America. 98: 8095-100. PMID 11427705 DOI: 10.1073/pnas.131116898  0.77
2001 Rubin J, Lee DD, Sompolinsky H. Equilibrium properties of temporally asymmetric Hebbian plasticity. Physical Review Letters. 86: 364-7. PMID 11177832 DOI: 10.1103/Physrevlett.86.364  0.47
2001 Shriki O, Sompolinsky H, Lee DD. An information maximization approach to overcomplete and recurrent representations Advances in Neural Information Processing Systems 0.667
1999 Dietrich R, Opper M, Sompolinsky H. Statistical mechanics of support vector networks Physical Review Letters. 82: 2975-2978. DOI: 10.1103/Physrevlett.82.2975  0.351
1998 van Vreeswijk C, Sompolinsky H. Chaotic balanced state in a model of cortical circuits. Neural Computation. 10: 1321-71. PMID 9698348 DOI: 10.1162/089976698300017214  0.742
1998 Kim JW, Sompolinsky H. On-line Gibbs learning. II. Application to perceptron and multilayer networks Physical Review E - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics. 58: 2348-2362. DOI: 10.1103/Physreve.58.2348  0.302
1997 Ben-Yishai R, Hansel D, Sompolinsky H. Traveling waves and the processing of weakly tuned inputs in a cortical network module. Journal of Computational Neuroscience. 4: 57-77. PMID 9046452 DOI: 10.1023/A:1008816611284  0.598
1996 van Vreeswijk C, Sompolinsky H. Chaos in neuronal networks with balanced excitatory and inhibitory activity. Science (New York, N.Y.). 274: 1724-6. PMID 8939866 DOI: 10.1126/science.274.5293.1724  0.746
1996 Hansel D, Sompolinsky H. Chaos and synchrony in a model of a hypercolumn in visual cortex. Journal of Computational Neuroscience. 3: 7-34. PMID 8717487 DOI: 10.1007/Bf00158335  0.633
1996 Mato G, Sompolinsky H. Neural network models of perceptual learning of angle discrimination. Neural Computation. 8: 270-99. PMID 8581884 DOI: 10.1162/Neco.1996.8.2.270  0.381
1995 Barkai N, Seung HS, Sompolinsky H. Local and global convergence of on-line learning. Physical Review Letters. 75: 1415-1418. PMID 10060287 DOI: 10.1103/PhysRevLett.75.1415  0.673
1995 Ben-Yishai R, Bar-Or RL, Sompolinsky H. Theory of orientation tuning in visual cortex. Proceedings of the National Academy of Sciences of the United States of America. 92: 3844-8. PMID 7731993 DOI: 10.1073/Pnas.92.9.3844  0.367
1994 Ginzburg I, Sompolinsky H. Theory of correlations in stochastic neural networks. Physical Review. E, Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics. 50: 3171-3191. PMID 9962363 DOI: 10.1103/PhysRevE.50.3171  0.352
1994 Sompolinsky H, Tsodyks M. Segmentation by a Network of Oscillators with Stored Memories Neural Computation. 6: 642-657. DOI: 10.1162/neco.1994.6.4.642  0.622
1993 Tsodyks M, Mitkov I, Sompolinsky H. Pattern of synchrony in inhomogeneous networks of oscillators with pulse interactions. Physical Review Letters. 71: 1280-1283. PMID 10055496 DOI: 10.1103/PhysRevLett.71.1280  0.594
1993 Hansel D, Sompolinsky H. Solvable model of spatiotemporal chaos. Physical Review Letters. 71: 2710-2713. PMID 10054756 DOI: 10.1103/Physrevlett.71.2710  0.525
1993 Barkai N, Seung HS, Sompolinsky H. Scaling laws in learning of classification tasks. Physical Review Letters. 70: 3167-3170. PMID 10053792 DOI: 10.1103/PhysRevLett.70.3167  0.659
1993 Seung HS, Sompolinsky H. Simple models for reading neuronal population codes. Proceedings of the National Academy of Sciences of the United States of America. 90: 10749-53. PMID 8248166 DOI: 10.1073/Pnas.90.22.10749  0.746
1993 Grannan ER, Kleinfeld D, Sompolinsky H. Stimulus-Dependent Synchronization of Neuronal Assemblies Neural Computation. 5: 550-569. DOI: 10.1162/neco.1993.5.4.550  0.589
1992 Hansel D, Sompolinsky H. Synchronization and computation in a chaotic neural network. Physical Review Letters. 68: 718-721. PMID 10045972 DOI: 10.1103/Physrevlett.68.718  0.622
1992 Aranson I, Golomb D, Sompolinsky H. Spatial coherence and temporal chaos in macroscopic systems with asymmetrical couplings. Physical Review Letters. 68: 3495-3498. PMID 10045719 DOI: 10.1103/PhysRevLett.68.3495  0.592
1992 Seung HS, Sompolinsky H, Tishby N. Statistical mechanics of learning from examples. Physical Review. A. 45: 6056-6091. PMID 9907706 DOI: 10.1103/PhysRevA.45.6056  0.783
1992 Barkai E, Hansel D, Sompolinsky H. Broken symmetries in multilayered perceptrons. Physical Review. A. 45: 4146-4161. PMID 9907466 DOI: 10.1103/PhysRevA.45.4146  0.445
1992 Golomb D, Hansel D, Shraiman B, Sompolinsky H. Clustering in globally coupled phase oscillators. Physical Review. A. 45: 3516-3530. PMID 9907399 DOI: 10.1103/Physreva.45.3516  0.753
1992 Sompolinsky H, Tsodyks M. PROCESSING OF SENSORY INFORMATION BY A NETWORK OF OSCILLATORS WITH MEMORY International Journal of Neural Systems. 3: 51-56. DOI: 10.1142/S0129065792000371  0.624
1992 Seung HS, Opper M, Sompolinsky H. Query by committee Proceedings of the Fifth Annual Acm Workshop On Computational Learning Theory. 287-294.  0.615
1991 Sompolinsky H, Golomb D, Kleinfeld D. Cooperative dynamics in visual processing. Physical Review. A. 43: 6990-7011. PMID 9905051 DOI: 10.1103/PhysRevA.43.6990  0.664
1990 Sompolinsky H, Tishby N, Seung HS. Learning from examples in large neural networks. Physical Review Letters. 65: 1683-1686. PMID 10042332 DOI: 10.1103/PhysRevLett.65.1683  0.769
1990 Golomb D, Rubin N, Sompolinsky H. Willshaw model: Associative memory with sparse coding and low firing rates. Physical Review. A. 41: 1843-1854. PMID 9903293 DOI: 10.1103/PhysRevA.41.1843  0.696
1990 Barkai E, Kanter I, Sompolinsky H. Properties of sparsely connected excitatory neural networks. Physical Review. A. 41: 590-597. PMID 9903143 DOI: 10.1103/Physreva.41.590  0.411
1990 Sompolinsky H, Golomb D, Kleinfeld D. Global processing of visual stimuli in a neural network of coupled oscillators. Proceedings of the National Academy of Sciences of the United States of America. 87: 7200-4. PMID 2402502 DOI: 10.1073/Pnas.87.18.7200  0.737
1990 Sompolinsky H, Tishby N. Learning in a two-layer neural network of edge detectors Epl. 13: 567-572. DOI: 10.1209/0295-5075/13/6/016  0.631
1989 Rubin N, Sompolinsky H. Neural networks with low local firing rates Epl. 10: 465-470. DOI: 10.1209/0295-5075/10/5/013  0.612
1988 Sompolinsky H, Crisanti A, Sommers HJ. Chaos in random neural networks. Physical Review Letters. 61: 259-262. PMID 10039285 DOI: 10.1103/PhysRevLett.61.259  0.355
1988 Crisanti A, Sompolinsky H. Dynamics of spin systems with randomly asymmetric bonds: Ising spins and Glauber dynamics. Physical Review. A. 37: 4865-4874. PMID 9899634 DOI: 10.1103/PhysRevA.37.4865  0.302
1988 Kleinfeld D, Sompolinsky H. Associative neural network model for the generation of temporal patterns. Theory and application to central pattern generators. Biophysical Journal. 54: 1039-51. PMID 3233265 DOI: 10.1016/S0006-3495(88)83041-8  0.607
1988 Sompolinsky H. Statistical Mechanics of Neural Networks Physics Today. 41: 70-80. DOI: 10.1063/1.881142  0.4
1987 Kotliar G, Sompolinsky H, Zippelius A. Rotational symmetry breaking in Heisenberg spin glasses: A microscopic approach. Physical Review. B, Condensed Matter. 35: 311-328. PMID 9940601 DOI: 10.1103/PhysRevB.35.311  0.44
1987 Crisanti A, Sompolinsky H. Dynamics of spin systems with randomly asymmetric bonds: Langevin dynamics and a spherical model. Physical Review. A. 36: 4922-4939. PMID 9898751 DOI: 10.1103/PhysRevA.36.4922  0.358
1987 Amit DJ, Gutfreund H, Sompolinsky H. Information storage in neural networks with low levels of activity. Physical Review. A. 35: 2293-2303. PMID 9898407 DOI: 10.1103/PhysRevA.35.2293  0.401
1987 Amit DJ, Gutfreund H, Sompolinsky H. Statistical mechanics of neural networks near saturation Annals of Physics. 173: 30-67. DOI: 10.1016/0003-4916(87)90092-3  0.39
1986 Sompolinsky H, Kanter I. Temporal association in asymmetric neural networks. Physical Review Letters. 57: 2861-2864. PMID 10033885 DOI: 10.1103/PhysRevLett.57.2861  0.402
1986 Sompolinsky H. Neural networks with nonlinear synapses and a static noise. Physical Review. A. 34: 2571-2574. PMID 9897569 DOI: 10.1103/PhysRevA.34.2571  0.343
1985 Amit DJ, Gutfreund H, Sompolinsky H. Storing infinite numbers of patterns in a spin-glass model of neural networks. Physical Review Letters. 55: 1530-1533. PMID 10031847 DOI: 10.1103/PhysRevLett.55.1530  0.319
1985 Fisher DS, Sompolinsky H. Scaling in spin-glasses. Physical Review Letters. 54: 1063-1066. PMID 10030919 DOI: 10.1103/PhysRevLett.54.1063  0.471
1985 Amit DJ, Gutfreund H, Sompolinsky H. Spin-glass models of neural networks. Physical Review. A. 32: 1007-1018. PMID 9896156 DOI: 10.1103/PhysRevA.32.1007  0.342
1984 Sompolinsky H, Kotliar G, Zippelius A. Exchange stiffness and macroscopic anisotropy in Heisenberg spin-glasses Physical Review Letters. 52: 392-395. DOI: 10.1103/Physrevlett.52.392  0.516
1983 Sompolinsky H, Zippelius A. Fluctuations in short-range spin-glasses Physical Review Letters. 50: 1297-1300. DOI: 10.1103/PhysRevLett.50.1297  0.503
1983 John S, Sompolinsky H, Stephen MJ. Localization in a disordered elastic medium near two dimensions Physical Review B. 27: 5592-5603. DOI: 10.1103/Physrevb.27.5592  0.45
1983 Dasgupta C, Sompolinsky H. Equivalence of statistical-mechanical and dynamic descriptions of the infinite-range Ising spin-glass Physical Review B. 27: 4511-4514. DOI: 10.1103/Physrevb.27.4511  0.543
1982 Sompolinsky H, Zippelius A. Relaxational dynamics of the Edwards-Anderson model and the mean-field theory of spin-glasses Physical Review B. 25: 6860-6875. DOI: 10.1103/PhysRevB.25.6860  0.525
1982 Henley CL, Sompolinsky H, Halperin BI. Spin-resonance frequencies in spin-glasses with random anisotropies Physical Review B. 25: 5849-5855. DOI: 10.1103/Physrevb.25.5849  0.638
1982 Sompolinsky H, Zippelius A. Relaxational dynamics of the infinite-ranged spin glass with n-component spins Journal of Physics C: Solid State Physics. 15: L1059-L1064. DOI: 10.1088/0022-3719/15/30/003  0.447
1981 Sompolinsky H, Zippelius A. Dynamic Theory of the Spin-Glass Phase Physical Review Letters. 47: 359-362. DOI: 10.1103/PhysRevLett.47.359  0.519
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